mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-05 16:48:03 +08:00
39 lines
1.7 KiB
C++
39 lines
1.7 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
|
//
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
//
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
|
|
#include "fastdeploy/pybind/main.h"
|
|
|
|
namespace fastdeploy {
|
|
void BindYOLOX(pybind11::module& m) {
|
|
pybind11::class_<vision::detection::YOLOX, FastDeployModel>(m, "YOLOX")
|
|
.def(pybind11::init<std::string, std::string, RuntimeOption,
|
|
ModelFormat>())
|
|
.def("predict",
|
|
[](vision::detection::YOLOX& self, pybind11::array& data,
|
|
float conf_threshold, float nms_iou_threshold) {
|
|
auto mat = PyArrayToCvMat(data);
|
|
vision::DetectionResult res;
|
|
self.Predict(&mat, &res, conf_threshold, nms_iou_threshold);
|
|
return res;
|
|
})
|
|
.def_readwrite("size", &vision::detection::YOLOX::size)
|
|
.def_readwrite("padding_value", &vision::detection::YOLOX::padding_value)
|
|
.def_readwrite("is_decode_exported",
|
|
&vision::detection::YOLOX::is_decode_exported)
|
|
.def_readwrite("downsample_strides",
|
|
&vision::detection::YOLOX::downsample_strides)
|
|
.def_readwrite("max_wh", &vision::detection::YOLOX::max_wh);
|
|
}
|
|
} // namespace fastdeploy
|